Along with the development of medical technology, various information such as patient information and image information are being converted into electronic data. In particular, along with the development of medical devices, the image data amount has increased, and in response thereto, the burden imposed on doctors to interpret radiograms has increased. Under such circumstances, an automatic diagnosis system (Computer-aided diagnosis (CAD)) intended to assist a doctor in the interpretation of a radiogram is being researched and developed targeted for various modalities such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), ultrasonography (US), Single Photon Emission Computed Tomography (SPECT), and Positron Emission Tomography (PET), or sites (a lung field, a breast, etc.).
As a method for diagnosing a brain disease in the automatic diagnosis system, there is proposed a method described in Patent Literature 1. In this method, a cinerea tissue is extracted from a subject's brain image data obtained from MRI, PET, SPECT, etc., and the extracted brain image is smoothened. Thereafter, anatomic standardization, etc., are performed on the brain image to statistically compare the brain image of the subject and that of a healthy person after which a Region of Interest (ROI) is set for analysis. Then, the analysis result is provided as a diagnostic outcome. In this case, a region set as the ROI is automatically set based on a Z score calculated from an average value and a standard deviation of voxel values of a healthy person image cluster about each voxel of the brain image.